82 resultados para Look-up tables


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This paper proposes a simple current error space vector based hysteresis controller for two-level inverter fed Induction Motor (IM) drives. This proposed hysteresis controller retains all advantages of conventional current error space vector based hysteresis controllers like fast dynamic response, simple to implement, adjacent voltage vector switching etc. The additional advantage of this proposed hysteresis controller is that it gives a phase voltage frequency spectrum exactly similar to that of a constant switching frequency space vector pulse width modulated (SVPWM) inverter. In this proposed hysteresis controller the boundary is computed online using estimated stator voltages along alpha and beta axes thus completely eliminating look up tables used for obtaining parabolic hysteresis boundary proposed in. The estimation of stator voltage is carried out using current errors along alpha and beta axes and steady state model of induction motor. The proposed scheme is simple and capable of taking inverter upto six step mode operation, if demanded by drive system. The proposed hysteresis controller based inverter fed drive scheme is simulated extensively using SIMULINK toolbox of MATLAB for steady state and transient performance. The experimental verification for steady state performance of the proposed scheme is carried out on a 3.7kW IM.

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A comprehensive design flow is proposed for the design of Micro Electro Mechanical Systems that are fabricated using SOIMUMPs process. Many of the designers typically do not model the temperature dependency of electrical conductivity, thermal conductivity and convection coefficient, as it is very cumbersome to create/incorporate the same in the existing FEM simulators. Capturing these dependencies is very critical particularly for structures that are electrically actuated. Lookup tables that capture the temperature dependency of electrical conductivity, thermal conductivity and convection coefficient are created. These look up tables are taken as inputs for a commercially available FEM simulator to model the semiconductor behavior. It is demonstrated that when temperature dependency for all the above mentioned parameters is not captured, then the error in estimation of the maximum temperature (for a given structure) could be as high as 30%. Error in the estimated resistance value under the same conditions is as high as 40%. When temperature dependency of the above mentioned parameters is considered then error w.r.t the measured values is less than 5%. It is evident that error in temperature estimates leads to erroneous results from mechanical simulations as well.

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A computationally efficient Li-ion battery model has been proposed in this paper. The battery model utilizes the features of both analytical and electrical circuit modeling techniques. The model is simple as it does not involve a look-up table technique and fast as it does not include a polynomial function during computation. The internal voltage of the battery is modeled as a linear function of the state-of-charge of the battery. The internal resistance is experimentally determined and the optimal value of resistance is considered for modeling. Experimental and simulated data are compared to validate the accuracy of the model.

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The inversion of canopy reflectance models is widely used for the retrieval of vegetation properties from remote sensing. This study evaluates the retrieval of soybean biophysical variables of leaf area index, leaf chlorophyll content, canopy chlorophyll content, and equivalent leaf water thickness from proximal reflectance data integrated broadbands corresponding to moderate resolution imaging spectroradiometer, thematic mapper, and linear imaging self scanning sensors through inversion of the canopy radiative transfer model, PROSAIL. Three different inversion approaches namely the look-up table, genetic algorithm, and artificial neural network were used and performances were evaluated. Application of the genetic algorithm for crop parameter retrieval is a new attempt among the variety of optimization problems in remote sensing which have been successfully demonstrated in the present study. Its performance was as good as that of the look-up table approach and the artificial neural network was a poor performer. The general order of estimation accuracy for para-meters irrespective of inversion approaches was leaf area index > canopy chlorophyll content > leaf chlorophyll content > equivalent leaf water thickness. Performance of inversion was comparable for broadband reflectances of all three sensors in the optical region with insignificant differences in estimation accuracy among them.

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Scalable stream processing and continuous dataflow systems are gaining traction with the rise of big data due to the need for processing high velocity data in near real time. Unlike batch processing systems such as MapReduce and workflows, static scheduling strategies fall short for continuous dataflows due to the variations in the input data rates and the need for sustained throughput. The elastic resource provisioning of cloud infrastructure is valuable to meet the changing resource needs of such continuous applications. However, multi-tenant cloud resources introduce yet another dimension of performance variability that impacts the application's throughput. In this paper we propose PLAStiCC, an adaptive scheduling algorithm that balances resource cost and application throughput using a prediction-based lookahead approach. It not only addresses variations in the input data rates but also the underlying cloud infrastructure. In addition, we also propose several simpler static scheduling heuristics that operate in the absence of accurate performance prediction model. These static and adaptive heuristics are evaluated through extensive simulations using performance traces obtained from Amazon AWS IaaS public cloud. Our results show an improvement of up to 20% in the overall profit as compared to the reactive adaptation algorithm.

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The development of techniques for scaling up classifiers so that they can be applied to problems with large datasets of training examples is one of the objectives of data mining. Recently, AdaBoost has become popular among machine learning community thanks to its promising results across a variety of applications. However, training AdaBoost on large datasets is a major problem, especially when the dimensionality of the data is very high. This paper discusses the effect of high dimensionality on the training process of AdaBoost. Two preprocessing options to reduce dimensionality, namely the principal component analysis and random projection are briefly examined. Random projection subject to a probabilistic length preserving transformation is explored further as a computationally light preprocessing step. The experimental results obtained demonstrate the effectiveness of the proposed training process for handling high dimensional large datasets.

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KIRCHHOFF’S theory [1] and the first-order shear deformation theory (FSDT) [2] of plates in bending are simple theories and continuously used to obtain design information. Within the classical small deformation theory of elasticity, the problem consists of determining three displacements, u, v, and w, that satisfy three equilibrium equations in the interior of the plate and three specified surface conditions. FSDT is a sixth-order theory with a provision to satisfy three edge conditions and maintains, unlike in Kirchhoff’s theory, independent linear thicknesswise distribution of tangential displacement even if the lateral deflection, w, is zero along a supported edge. However, each of the in-plane distributions of the transverse shear stresses that are of a lower order is expressed as a sum of higher-order displacement terms. Kirchhoff’s assumption of zero transverse shear strains is, however, not a limitation of the theory as a first approximation to the exact 3-D solution.

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Abstract-To detect errors in decision tables one needs to decide whether a given set of constraints is feasible or not. This paper describes an algorithm to do so when the constraints are linear in variables that take only integer values. Decision tables with such constraints occur frequently in business data processing and in nonnumeric applications. The aim of the algorithm is to exploit. the abundance of very simple constraints that occur in typical decision table contexts. Essentially, the algorithm is a backtrack procedure where the the solution space is pruned by using the set of simple constrains. After some simplications, the simple constraints are captured in an acyclic directed graph with weighted edges. Further, only those partial vectors are considered from extension which can be extended to assignments that will at least satisfy the simple constraints. This is how pruning of the solution space is achieved. For every partial assignment considered, the graph representation of the simple constraints provides a lower bound for each variable which is not yet assigned a value. These lower bounds play a vital role in the algorithm and they are obtained in an efficient manner by updating older lower bounds. Our present algorithm also incorporates an idea by which it can be checked whether or not an (m - 2)-ary vector can be extended to a solution vector of m components, thereby backtracking is reduced by one component.

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THE use of NMR to investigate the quality of the oil as a function of maturity of the seeds is demonstrated for sunflower seeds. The percentages of the saturated and individual unsaturated aids are determined as a function of time after flowering of the seeds. The percentage of saturated fatty acids is found to decrease with maturity of seeds whereas the extent of the unsaturated acids increases.

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Thermal polymerization of acrylamide has been followed by the DSC technique, and the activation energy (E) values at different stages of the fraction polymerized (a) have been determined from the exotherm of the thermograms obtained. The trend of variation of E with agr shows that E remains constant up to agr = 0.5 and decreases with a further increase in agr. A close look at the composite nature of the exotherms, agr-t, and agr-T curves shows that the polymerization of acrylamide involves two processes. The first process is the formation of linear polyacrylamide and the second is the simultaneous cross-linking of the linear chains together with the formation of linear polyacrylamide. Experiments such as NH3 detection by differential thermal analysis techniques and annealing studies have been made to shed further light on the polymerization process.

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Sequential up/down counting is required many a time. In this paper, the logical design of such a counter of the parallel carry type is furnished.

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We present two discriminative language modelling techniques for Lempel-Ziv-Welch (LZW) based LID system. The previous approach to LID using LZW algorithm was to directly use the LZW pattern tables forlanguage modelling. But, since the patterns in a language pattern table are shared by other language pattern tables, confusability prevailed in the LID task. For overcoming this, we present two pruning techniques (i) Language Specific (LS-LZW)-in which patterns common to more than one pattern table are removed. (ii) Length-Frequency product based (LF-LZW)-in which patterns having their length-frequency product below a threshold are removed. These approaches reduce the classification score (Compression Ratio [LZW-CR] or the weighted discriminant score [LZW-WDS]) for non native languages and increases the LID performance considerably. Also the memory and computational requirements of these techniques are much less compared to basic LZW techniques.

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This article examines, through a molecular perspective, the 'ozone-friendly' refrigerants R-134a and R-123 vis-à-vis R-12 and R-11, which are targeted to be phased out under the Montreal Protocol on Substances that Deplete the Ozone Layer, Final Act (1987). It appears that the molecular weight, size parameter, and dipole moment, of R-134a and R-123, may induce a pronounced effect on the chemical equilibrium of ice particles in the polar stratospheric clouds and subsequently influence the photochemical reactions therein. Non-polar, high-molecular-weight perfluoropropane (R-218), could be a better substitute for R-12, while R-134, which is a non-polar HFC of the ethane family, could also be a candidate although its molecular weight is lower than that of R-12. The search for a good substitute for R-11, however, must continue.

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Stable carbon isotope ratios of peats dated (by C-14) back to 40 kyr BP from the montane region (> 1800 m asl) of the Nilgiris, southern India, reflect changes in the relative proportions of C3 and C4 plant types, which are influenced by soil moisture (and hence monsoonal precipitation), From prior to 40 kyr BP until 28 kyr BP, a general decline in delta(13)C values from about - 14 per mil to - 19 per mil suggests increased dominance of C3 plants concurrent with increasingly moist conditions, During 28-18 kyr BP there seems relatively little change with delta(13) C of - 19 to - 18 per mil, At about 16 kyr BP a sharp reversal in delta(13)C to a peak of - 14.7 per mil indicates a clear predominance of C4 vegetation associated with arid conditions, possibly during or just after the Last Glacial Maximum, A moist phase at about 9 kyr BP (the Holocene Optimum) with dominance of C3 vegetation type is observed, while arid conditions are re-established during 5-2 kyr BP with an overall dominance of C4 vegetation, New data do not support the occurrence of a moist phase coinciding with the Mediaeval Warm Period (at 0.6 kyr BP) as suggested earlier, Overall, the climate and vegetation in the high altitude regions of the southern Indian tropics seem to have responded to past global climatic changes, and this is consistent with other evidences from India and other tropical regions.

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A compact clamp-type high pressure cell for carrying out electrical conductivity measurements on small solid samples of size 1 mm or less at pressures upto 8 GPa (i.e., 80 kbar) and for use down to 77 K has been designed and fabricated. The pressure generated in the sample region has been calibrated at room temperature against the polymorphic phase transitions of Bismuth and Ytterbium. The pressure relaxation of the clamp at low temperatures has been estimated by monitoring the electrical conductivity behavior of lead. Review of Scientific Instruments is copyrighted by The American Institute of Physics.